端到端训练 xgboost/dnn/lr 二分类模型——读上游 feature-analysis 产出的 splits/{train,test,oot}.parquet，产八阶段产物(features/model/evaluation/predictions/explainability/comparison/logs/config)，并与历史 baseline 做 AUC/KS/分档多维对比。本 skill 不取数也不切分。当用户说"建模""训练新模型""跑模型""对比base""迭代模型"时使用。
How to install classification-model-training?
qfin-tech/model-evo/classification-model-training
$npx -y skills add qfin-tech/model-evo --skill classification-model-trainingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/qfin-tech/model-evo" --skill "qfin-tech/model-evo/classification-model-training"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/qfin-tech/model-evo" that are relevant to the current task. Run `npx skills add "https://github.com/qfin-tech/model-evo"` and select the relevant skills, then follow their instructions.
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